AI Agents · Lesson

Argument Parsing and Help Text

Required vs optional args, type validation, and auto-generated help.

Good CLI Design Starts with Good Arguments

A well-designed CLI agent argument interface means users can figure out how to use the tool from --help alone. Every argument should have a clear name, type, default value, and description.

Poorly named or undocumented arguments make tools frustrating to use and hard to maintain.

Required vs. Optional Arguments

Required arguments must be provided — the CLI exits with an error if they are missing. Optional arguments have a default= value and can be omitted. Deciding which is which shapes your tool's UX.

import argparse

parser = argparse.ArgumentParser(description='AI Agent CLI')

# Required: no default, must be provided
parser.add_argument(
    '--query', '-q',
    type=str,
    required=True,
    help='Question to send to the agent'
)

# Optional: has a default, can be omitted
parser.add_argument(
    '--model', '-m',
    type=str,
    default='gpt-4o-mini',
    help='Model name (default: gpt-4o-mini)'
)

parser.add_argument(
    '--max-tokens',
    type=int,
    default=1000,
    help='Maximum tokens in response (default: 1000)'
)

args = parser.parse_args(['--query', 'test'])
print(args.query, args.model, args.max_tokens)

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